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Probabilistic Prediction of Corrosion Damage of Steel Structures in the Vicinity of Roads

Author

Listed:
  • Monika Kubzova

    (Department of Structures, Faculty of Civil Engineering, VSB-Technical University of Ostrava, 708 00 Ostrava-Poruba, Czech Republic)

  • Vit Krivy

    (Department of Structures, Faculty of Civil Engineering, VSB-Technical University of Ostrava, 708 00 Ostrava-Poruba, Czech Republic)

  • Katerina Kreislova

    (SVUOM Ltd., U Mestanskeho Pivovaru 934/4, 170 00 Prague 7, Czech Republic)

Abstract

The design, construction, and maintenance of steel structures must be carried out in a way that ensures they will be able to reliably operate for the whole duration of their planned service life. To ensure sufficient durability, it is necessary to determine and evaluate the characteristics of the appropriate environment in which the structure will be placed. This submission focuses on the specific environment surrounding roads that are treated with de-icing salts during winter maintenance. It investigates the dependency between corrosive damage to the structure and the relevant parameters of the environment. Basic corrosive factors include temperature, relative humidity, deposition of chlorides and sulfur dioxide, precipitation, the pH of precipitation as well as many other parameters. An accurate estimate of corrosive damage requires an analysis of the long-term trends in concentrations of individual corrosive factors, while respecting their randomly varying attributes. The article, hence, introduces and evaluates stochastic prediction models that are based on long-term programs focusing on the evaluation of the corrosive aggressiveness of the environment, while taking into account random variations of the nature of the input parameters. The use of stochastic prediction models allows us to perform sensitivity analysis that can determine the impact of specific corrosive factors on the corrosive damage caused to the structure. The article is supplemented by sensitivity analysis focusing on an evaluation from the effects of the deposition of chlorides on the corrosive damage to steel bridge structures. The analysis was carried out using data obtained from experimental measurements of the deposition rates of chlorides in the vicinity of roads in the Czech Republic.

Suggested Citation

  • Monika Kubzova & Vit Krivy & Katerina Kreislova, 2020. "Probabilistic Prediction of Corrosion Damage of Steel Structures in the Vicinity of Roads," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:9851-:d:450818
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    References listed on IDEAS

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    1. Olive, David J., 2007. "Prediction intervals for regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3115-3122, March.
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